# Week 5-(Statistics) response to Jeff Brown and Andrew Rowe

Please respond to these 2 answers in 2 separate paragraphs with a minimum of 175 words each paragraph.

Jeff Brown’s response, I’ve had to use hypothetical testing in my professional life when examining productivity. My null testing was whether or not restroom breaks were affecting the productivity. Which in turn you would assume the restroom breaks would immediately take up time where an assembly is not being produced. Of course throughout the testing I take plenty of notes to track the productivity and to ensure my hypothesis is still on track. My results concluded that restroom breaks did not affect productivity as much as I thought which made my research null since I thought originally that as much as some went I believed it affected their numbers. Most of it may contribute to regular fatigue and repudiation. These two factors slow down the workers and affected their numbers by twenty percent. These numbers were astounding to me as I originally thought that it was the restroom breaks. I have to admit I was not sure what it was called until this class I just was collecting data and comparing to a hypothesis I had in my teams productivity.

Andrew Rowe’s response, A hypothesis is a claim about a specific part of a population. When you are looking at aspects of a population and have an idea of what makes certain parts of it unique from the rest of the population, you test the hypothesis to see if it is true. There are many times that you would use hypothesis testing. I just moved into a new home on Friday, and the cost of my homeowners insurance rose quite significantly. I don’t know too much about the insurance industry, but I would venture to guess that they are always using this method and taking the results from different sub populations that they insure to determine costs. A one-tailed test is simply testing a specific variable to see if there is a significant difference in one direction. On the other hand, a two tailed-test tests variables to see if there is a significant difference in either direction.

At work, I make the schedule for a group of 48 people. In the hospital setting, it is hard to predict the need for staff as the number of patients in the hospital varies from time to time. Typically in the fall/winter time, it is busier in a children’s hospital as the kids in the community go back to school and expose each other to a slew of viruses. During the summer months, we are always well staffed and able to safely care for all of the patients requiring my group’s services. By October and all the way through April, we are chronically short staffed due to an increase in patients. A few years ago we tested the need for for staff in May-September vs October-April. We did this so that we could take the results to administration and make a case for spending extra capital to bring in travelers during the “surge” to help us out. We are now at the point that we have funds for travelers built into our annual budget for the “surge”.

Here is the original question. (You don’t need to answer, this is just to give you context)